Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts

Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.

Mechanisms of the negative shortwave cloud feedback in mid to high latitudes

Increases in cloud optical depth and liquid water path (LWP) are robust features of global warming model simulations in high latitudes, yielding a negative shortwave cloud feedback, but the mechanisms are still uncertain. We assess the importance of microphysical processes for the negative optical depth feedback by perturbing temperature in the microphysics schemes of two aquaplanet models, both of which have separate prognostic equations for liquid water and ice. We find that most of the LWP increase with warming is caused by a suppression of ice microphysical processes in mixed-phase clouds, resulting in reduced conversion efficiencies of liquid water to ice and precipitation. Perturbing the temperature-dependent phase partitioning of convective condensate also yields a small LWP increase. Together, the perturbations in large-scale microphysics and convective condensate partitioning explain more than two-thirds of the LWP response relative to a reference case with increased SSTs, and capture all of the vertical structure of the liquid water response. In support of these findings, we show the existence of a very robust positive relationship between monthly-mean LWP and temperature in CMIP5 models and observations in mixed-phase cloud regions only. In models, the historical LWP sensitivity to temperature is a good predictor of the forced global warming response poleward of about 45°, although models appear to overestimate the LWP response to warming compared to observations. We conclude that in climate models, the suppression of ice-phase microphysical processes that deplete cloud liquid water is a key driver of the LWP increase with warming and of the associated negative shortwave cloud feedback.

Revisiting Swiss temperature trends 1959-2008

Temperature is a key variable for monitoring global climate change. Here we perform a trend analysis of Swiss temperatures from 1959 to 2008, using a new 2 × 2 km gridded data-set based on carefully homogenised ground observations from MeteoSwiss. The aim of this study is twofold: first, to discuss the spatial and altitudinal temperature trend characteristics in detail, and second, to quantify the contribution of changes in atmospheric circulation and local effects to these trends. The seasonal trends are all positive and mostly significant with an annual average warming rate of 0.35 °C/decade (∼1.6 times the northern hemispheric warming rate), ranging from 0.17 in autumn to 0.48 °C/decade in summer. Altitude-dependent trends are found in autumn and early winter where the trends are stronger at low altitudes (<800 m asl), and in spring where slightly stronger trends are found at altitudes close to the snow line. Part of the trends can be explained by changes in atmospheric circulation, but with substantial differences from season to season. In winter, circulation effects account for more than half the trends, while this contribution is much smaller in other seasons. After removing the effect of circulation, the trends still show seasonal variations with higher values in spring and summer. The circulation-corrected trends are closer to the values simulated by a set of ENSEMBLES regional climate models, with the models still tending towards a trend underestimation in spring and summer. Our results suggest that both circulation changes and more local effects are important to explain part of recent warming in spring, summer, and autumn. Snow-albedo feedback effects could be responsible for the stronger spring trends at altitudes close to the snow line, but the overall effect is small. In autumn, the observed decrease in fog frequency might be a key process in explaining the stronger temperature trends at low altitudes.

Regionally coupled atmosphere-ocean-sea ice-marine biogeochemistry model ROM: 1. Description and validation

The general circulation models used to simulate global climate typically feature resolution too coarse to reproduce many smaller-scale processes, which are crucial to determining the regional responses to climate change. A novel approach to downscale climate change scenarios is presented which includes the interactions between the North Atlantic Ocean and the European shelves as well as their impact on the North Atlantic and European climate. The goal of this paper is to introduce the global ocean-regional atmosphere coupling concept and to show the potential benefits of this model system to simulate present-day climate. A global ocean-sea ice-marine biogeochemistry model (MPIOM/HAMOCC) with regionally high horizontal resolution is coupled to an atmospheric regional model (REMO) and global terrestrial hydrology model (HD) via the OASIS coupler. Moreover, results obtained with ROM using NCEP/NCAR reanalysis and ECHAM5/MPIOM CMIP3 historical simulations as boundary conditions are presented and discussed for the North Atlantic and North European region. The validation of all the model components, i.e., ocean, atmosphere, terrestrial hydrology, and ocean biogeochemistry is performed and discussed. The careful and detailed validation of ROM provides evidence that the proposed model system improves the simulation of many aspects of the regional climate, remarkably the ocean, even though some biases persist in other model components, thus leaving potential for future improvement. We conclude that ROM is a powerful tool to estimate possible impacts of climate change on the regional scale.

Clouds and the atmospheric circulation response to warming

We study the effect of clouds on the atmospheric circulation response to CO2 quadrupling in an aquaplanet model with a slab-ocean lower boundary. The cloud effect is isolated by locking the clouds to either the control or 4xCO2 state in the shortwave (SW) or longwave (LW) radiation schemes. In our model, cloud-radiative changes explain more than half of the total poleward expansion of the Hadley cells, midlatitude jets, and storm tracks under CO2 quadrupling, even though they cause only one-fourth of the total global-mean surface warming. The effect of clouds on circulation results mainly from the SW cloud-radiative changes, which strongly enhance the Equator-to-pole temperature gradient at all levels in the troposphere, favoring stronger and poleward-shifted midlatitude eddies. By contrast, quadrupling CO2 while holding the clouds fixed causes strong polar amplification and weakened midlatitude baroclinicity at lower levels, yielding only a small poleward expansion of the circulation. Our results show that (a) the atmospheric circulation responds sensitively to cloud-driven changes in meridional and vertical temperature distribution, and (b) the spatial structure of cloud feedbacks likely plays a dominant role in the circulation response to greenhouse gas forcing. While the magnitude and spatial structure of the cloud feedback are expected to be highly model-dependent, an analysis of 4xCO2 simulations of CMIP5 models shows that the SW cloud feedback likely forces a poleward expansion of the tropospheric circulation in most climate models.

Interacting effects of climate change and habitat fragmentation on drought-sensitive butterflies

Climate change is expected to increase the frequency of some climatic extremes. These may have drastic impacts on biodiversity, particularly if meteorological thresholds are crossed, leading to population collapses. Should this occur repeatedly, populations may be unable to recover, resulting in local extinctions. Comprehensive time series data on butterflies in Great Britain provide a rare opportunity to quantify population responses to both past severe drought and the interaction with habitat area and fragmentation. Here, we combine this knowledge with future projections from multiple climate models, for different Representative Concentration Pathways (RCPs), and for simultaneous modelled responses to different landscape characteristics. Under RCP8.5, which is associated with ‘business as usual’ emissions, widespread drought-sensitive butterfly population extinctions could occur as early as 2050. However, by managing landscapes and particularly reducing habitat fragmentation, the probability of persistence until mid-century improves from around zero to between 6 and 42% (95% confidence interval). Achieving persistence with a greater than 50% chance and right through to 2100 is possible only under both low climate change (RCP2.6) and semi-natural habitat restoration. Our data show that, for these drought-sensitive butterflies, persistence is achieved more effectively by restoring semi-natural landscapes to reduce fragmentation, rather than simply focusing on increasing habitat area, but this will only be successful in combination with substantial emission reductions.

Projected changes in tropical cyclones over Vietnam and the South China Sea using a 25 km regional climate model perturbed physics ensemble

The regional climate modelling system PRECIS, was run at 25 km horizontal resolution for 150 years (1949-2099) using global driving data from a five member perturbed physics ensemble (based on the coupled global climate model HadCM3). Output from these simulations was used to investigate projected changes in tropical cyclones (TCs) over Vietnam and the South China Sea due to global warming (under SRES scenario A1B). Thirty year climatological mean periods were used to look at projected changes in future (2069-2098) TCs compared to a 1961-1990 baseline. Present day results were compared qualitatively with IBTrACS observations and found to be reasonably realistic. Future projections show a 20-44 % decrease in TC frequency, although the spatial patterns of change differ between the ensemble members, and an increase of 27-53 % in the amount of TC associated precipitation. No statistically significant changes in TC intensity were found, however, the occurrence of more intense TCs (defined as those with a maximum 10 m wind speed > 35 m/s) was found to increase by 3-9 %. Projected increases in TC associated precipitation are likely caused by increased evaporation and availability of atmospheric water vapour, due to increased sea surface and atmospheric temperature. The mechanisms behind the projected changes in TC frequency are difficult to link explicitly; changes are most likely due to the combination of increased static stability, increased vertical wind shear and decreased upward motion, which suggest a decrease in the tropical overturning circulation.

Climate-driven expansion of blanket bogs in Britain during the Holocene

Blanket bog occupies approximately 6 % of the area of the UK today. The Holocene expansion of this hyperoceanic biome has previously been explained as a consequence of Neolithic forest clearance. However, the present distribution of blanket bog in Great Britain can be predicted accurately with a simple model (PeatStash) based on summer temperature and moisture index thresholds, and the same model correctly predicts the highly disjunct distribution of blanket bog worldwide. This finding suggests that climate, rather than land-use history, controls blanket-bog distribution in the UK and everywhere else. We set out to test this hypothesis for blanket bogs in the UK using bioclimate envelope modelling compared with a database of peat initiation age estimates. We used both pollen-based reconstructions and climate model simulations of climate changes between the mid-Holocene (6000 yr BP, 6 ka) and modern climate to drive PeatStash and predict areas of blanket bog. We compiled data on the timing of blanket-bog initiation, based on 228 age determinations at sites where peat directly overlies mineral soil. The model predicts large areas of northern Britain would have had blanket bog by 6000 yr BP, and the area suitable for peat growth extended to the south after this time. A similar pattern is shown by the basal peat ages and new blanket bog appeared over a larger area during the late Holocene, the greatest expansion being in Ireland, Wales and southwest England, as the model predicts. The expansion was driven by a summer cooling of about 2 °C, shown by both pollen-based reconstructions and climate models. The data show early Holocene (pre-Neolithic) blanket-bog initiation at over half of the sites in the core areas of Scotland, and northern England. The temporal patterns and concurrence of the bioclimate model predictions and initiation data suggest that climate change provides a parsimonious explanation for the early Holocene distribution and later expansion of blanket bogs in the UK, and it is not necessary to invoke anthropogenic activity as a driver of this major landscape change.

Irreducible uncertainty in near-term climate projections

Model simulations of the next few decades are widely used in assessments of climate change impacts and as guidance for adaptation. Their non-linear nature reveals a level of irreducible uncertainty which it is important to understand and quantify, especially for projections of near-term regional climate. Here we use large idealised initial condition ensembles of the FAMOUS global climate model with a 1 %/year compound increase in CO2 levels to quantify the range of future temperatures in model-based projections. These simulations explore the role of both atmospheric and oceanic initial conditions and are the largest such ensembles to date. Short-term simulated trends in global temperature are diverse, and cooling periods are more likely to be followed by larger warming rates. The spatial pattern of near-term temperature change varies considerably, but the proportion of the surface showing a warming is more consistent. In addition, ensemble spread in inter-annual temperature declines as the climate warms, especially in the North Atlantic. Over Europe, atmospheric initial condition uncertainty can, for certain ocean initial conditions, lead to 20 year trends in winter and summer in which every location can exhibit either strong cooling or rapid warming. However, the details of the distribution are highly sensitive to the ocean initial condition chosen and particularly the state of the Atlantic meridional overturning circulation. On longer timescales, the warming signal becomes more clear and consistent amongst different initial condition ensembles. An ensemble using a range of different oceanic initial conditions produces a larger spread in temperature trends than ensembles using a single ocean initial condition for all lead times. This highlights the potential benefits from initialising climate predictions from ocean states informed by observations. These results suggest that climate projections need to be performed with many more ensemble members than at present, using a range of ocean initial conditions, if the uncertainty in near-term regional climate is to be adequately quantified.

Increasing frequency of extreme El Niño events due to greenhouse warming

El Niño events are a prominent feature of climate variability with global climatic impacts. The 1997/98 episode, often referred to as ‘the climate event of the twentieth century’1, 2, and the 1982/83 extreme El Niño3, featured a pronounced eastward extension of the west Pacific warm pool and development of atmospheric convection, and hence a huge rainfall increase, in the usually cold and dry equatorial eastern Pacific. Such a massive reorganization of atmospheric convection, which we define as an extreme El Niño, severely disrupted global weather patterns, affecting ecosystems4, 5, agriculture6, tropical cyclones, drought, bushfires, floods and other extreme weather events worldwide3, 7, 8, 9. Potential future changes in such extreme El Niño occurrences could have profound socio-economic consequences. Here we present climate modelling evidence for a doubling in the occurrences in the future in response to greenhouse warming. We estimate the change by aggregating results from climate models in the Coupled Model Intercomparison Project phases 3 (CMIP3; ref. 10) and 5 (CMIP5; ref. 11) multi-model databases, and a perturbed physics ensemble12. The increased frequency arises from a projected surface warming over the eastern equatorial Pacific that occurs faster than in the surrounding ocean waters13, 14, facilitating more occurrences of atmospheric convection in the eastern equatorial region.

Climate-driven expansion of blanket bogs in Britain during the Holocene

Blanket bog occupies approximately 6% of the area of the UK today. The Holocene expansion of this hyperoceanic biome has previously been explained as a consequence of Neolithic forest clearance. However, the present distribution of blanket bog in Great Britain can be predicted accurately with a simple model (PeatStash) based on summer temperature and moisture index thresholds, and the same model correctly predicts the highly disjunct distribution of blanket bog worldwide. This finding suggests that climate, rather than land-use history, controls blanket-bog distribution in the UK and everywhere else. We set out to test this hypothesis for blanket bogs in the UK using bioclimate envelope modelling compared with a database of peat initiation age estimates. We used both pollen-based reconstructions and climate model simulations of climate changes between the mid-Holocene (6000 yr BP, 6 ka) and modern climate to drive PeatStash and predict areas of blanket bog. We compiled data on the timing of blanketbog initiation, based on 228 age determinations at sites where peat directly overlies mineral soil. The model predicts that large areas of northern Britain would have had blanket bog by 6000 yr BP, and the area suitable for peat growth extended to the south after this time. A similar pattern is shown by the basal peat ages and new blanket bog appeared over a larger area during the late Holocene, the greatest expansion being in Ireland,Wales, and southwest England, as the model predicts. The expansion was driven by a summer cooling of about 2 °C, shown by both pollen-based reconstructions and climate models. The data show early Holocene (pre- Neolithic) blanket-bog initiation at over half of the sites in the core areas of Scotland and northern England. The temporal patterns and concurrence of the bioclimate model predictions and initiation data suggest that climate change provides a parsimonious explanation for the early Holocene distribution and later expansion of blanket bogs in the UK, and it is not necessary to invoke anthropogenic activity as a driver of this major landscape change.

Legacy effects of grassland management on soil carbon to depth

The importance of managing land to optimise carbon sequestration for climate change mitigation is widely recognised, with grasslands being identified as having the potential to sequester additional carbon. However, most soil carbon inventories only consider surface soils, and most large scale surveys group ecosystems into broad habitats without considering management intensity. Consequently, little is known about the quantity of deep soil carbon and its sensitivity to management. From a nationwide survey of grassland soils to 1 m depth, we show that carbon in grasslands soils is vulnerable to management and that these management effects can be detected to considerable depth down the soil profile, albeit at decreasing significance with depth. Carbon concentrations in soil decreased as management intensity increased, but greatest soil carbon stocks (accounting for bulk density differences), were at intermediate levels of management. Our study also highlights the considerable amounts of carbon in sub-surface soil below 30cm, which is missed by standard carbon inventories. We estimate grassland soil carbon in Great Britain to be 2097 Tg C to a depth of 1 m, with ~60% of this carbon being below 30cm. Total stocks of soil carbon (t ha-1) to 1 m depth were 10.7% greater at intermediate relative to intensive management, which equates to 10.1 t ha-1 in surface soils (0-30 cm), and 13.7 t ha-1 in soils from 30-100 cm depth. Our findings highlight the existence of substantial carbon stocks at depth in grassland soils that are sensitive to management. This is of high relevance globally, given the extent of land cover and large stocks of carbon held in temperate managed grasslands. Our findings have implications for the future management of grasslands for carbon storage and climate mitigation, and for global carbon models which do not currently account for changes in soil carbon to depth with management.

The impact of variable sea ice roughness on changes in Arctic Ocean surface stress: a model study

The Arctic sea ice cover is thinning and retreating, causing changes in surface roughness that in turn modify the momentum flux from the atmosphere through the ice into the ocean. New model simulations comprising variable sea ice drag coefficients for both the air and water interface demonstrate that the heterogeneity in sea ice surface roughness significantly impacts the spatial distribution and trends of ocean surface stress during the last decades. Simulations with constant sea ice drag coefficients as used in most climate models show an increase in annual mean ocean surface stress (0.003 N/m2 per decade, 4.6%) due to the reduction of ice thickness leading to a weakening of the ice and accelerated ice drift. In contrast, with variable drag coefficients our simulations show annual mean ocean surface stress is declining at a rate of -0.002 N/m2 per decade (3.1%) over the period 1980-2013 because of a significant reduction in surface roughness associated with an increasingly thinner and younger sea ice cover. The effectiveness of sea ice in transferring momentum does not only depend on its resistive strength against the wind forcing but is also set by its top and bottom surface roughness varying with ice types and ice conditions. This reveals the need to account for sea ice surface roughness variations in climate simulations in order to correctly represent the implications of sea ice loss under global warming.

Terrestrial biosphere changes over the last 120 kyr

A new global synthesis and biomization of long (> 40 kyr) pollen-data records is presented and used with sim- ulations from the HadCM3 and FAMOUS climate models and the BIOME4 vegetation model to analyse the dynamics of the global terrestrial biosphere and carbon storage over the last glacial–interglacial cycle. Simulated biome distribu- tions using BIOME4 driven by HadCM3 and FAMOUS at the global scale over time generally agree well with those in- ferred from pollen data. Global average areas of grassland and dry shrubland, desert, and tundra biomes show large- scale increases during the Last Glacial Maximum, between ca. 64 and 74 ka BP and cool substages of Marine Isotope Stage 5, at the expense of the tropical forest, warm-temperate forest, and temperate forest biomes. These changes are re- flected in BIOME4 simulations of global net primary pro- ductivity, showing good agreement between the two models. Such changes are likely to affect terrestrial carbon storage, which in turn influences the stable carbon isotopic composi- tion of seawater as terrestrial carbon is depleted in 13C.

Understanding advances in the simulation of the Madden-Julian Oscillation in a numerical weather prediction model.

The Madden-Julian Oscillation (MJO) is the dominant mode of intraseasonal variability in the Trop- ics. It can be characterised as a planetary-scale coupling between the atmospheric circulation and organised deep convection that propagates east through the equatorial Indo-Pacific region. The MJO interacts with weather and climate systems on a near-global scale and is a crucial source of predictability for weather forecasts on medium to seasonal timescales. Despite its global signifi- cance, accurately representing the MJO in numerical weather prediction (NWP) and climate models remains a challenge. This thesis focuses on the representation of the MJO in the Integrated Forecasting System (IFS) at the European Centre for Medium-Range Weather Forecasting (ECMWF), a state-of-the-art NWP model. Recent modifications to the model physics in Cycle 32r3 (Cy32r3) of the IFS led to ad- vances in the simulation of the MJO; for the first time the observed amplitude of the MJO was maintained throughout the integration period. A set of hindcast experiments, which differ only in their formulation of convection, have been performed between May 2008 and April 2009 to asses the sensitivity of MJO simulation in the IFS to the Cy32r3 convective parameterization. Unique to this thesis is the attribution of the advances in MJO simulation in Cy32r3 to the mod- ified convective parameterization, specifically, the relative-humidity-dependent formulation for or- ganised deep entrainment. Increasing the sensitivity of the deep convection scheme to environmen- tal moisture is shown to modify the relationship between precipitation and moisture in the model. Through dry-air entrainment, convective plumes ascending in low-humidity environments terminate lower in the atmosphere. As a result, there is an increase in the occurrence of cumulus congestus, which acts to moisten the mid-troposphere. Due to the modified precipitation-moisture relationship more moisture is able to build up which effectively preconditions the tropical atmosphere for the transition to deep convection. Results from this thesis suggest that a tropospheric moisture control on convection is key to simulating the interaction between the physics and large-scale circulation associated with the MJO.